A Parallel-Oriented Language for Modeling Constraint-Based Solvers

International audienceThis paper presents the Parallel-Oriented Solver Language (POSL, pronounced " puzzle "): a new framework to build interconnected meta-heuristic based solvers working in parallel. The goal of this work is to obtain a framework to easily build solvers and reduce the developing effort, by providing a mechanism for reusing code from other solvers. The novelty of this approach lies in looking at solver as a set of components with specific goals, written in a parallel-oriented language based on operators. An interesting advantage of POSL is the possibility to share not only information, but also behaviors, allowing solvers modifications. POSL allows solver's components to be transferred and executed by other solvers. It provides an additional layer to dynamically define the connectivity between the solvers. The implementation of POSL remains a work in progress, therefore this paper will focus on POSL concepts only

An Empirical Survey on Co-simulation: Promising Standards, Challenges and Research Needs

Co-simulation is a promising approach for the modelling and simulation of complex systems, that makes use of mature simulation tools in the respective domains. It has been applied in wildly different domains, oftentimes without a comprehensive study of the impact to the simulation results. As a consequence, over the recent years, researchers have set out to understand the essential challenges arising from the application of this technique. This paper complements the existing surveys in that the social and empirical aspects were addressed. More than 50 experts participated in a two-stage Delphi study to determine current challenges, research needs and promising standards and tools. Furthermore, an analysis of the strengths, weakness, opportunities and threats of co-simulation utilizing the analytic hierarchy process resulting in a SWOT-AHP analysis is presented. The empirical results of this study show that experts consider the FMI standard to be the most promising standard for continuous time, discrete event and hybrid co-simulation. The results of the SWOT-AHP analysis indicate that factors related to strengths and opportunities predominate

Un langage orienté parallèle pour modéliser des solveurs de contraintes

National audienceCet article présente Parallel-Oriented Solver Language (POSL, prononcé "puzzle") : un système pour construire des méta-heuristiques interconnectées tra-vaillant en parallèle. Le but de ce travail est d'obtenir un système pour facilement construire des solveurs et réduire l'effort de leur développement en proposant un mécanisme de réutilisation de code entre les différents solveurs. La nouveauté de cette approche porte sur le fait que l'on voit un solveur comme un ensemble de composants spécifiques, écris dans un langage orienté parallèle basé sur des opérateurs. Un avantage de POSL est la possibilité de parta-ger non seulement des informations mais aussi des comportements, permettant ainsi de modifier à chaud les solveurs. POSL permets aux composants d'un sol-veur d'être transmis et exécutés par d'autres solveurs. Il propose également une couche supplémentaire per-mettant de définir dynamiquement des connexions entre solveurs. L'implémentation de POSL restant un travail en cours, cet article se concentre uniquement sur ses concepts

An overlapped grid method for multigrid, finite volume/difference flow solvers: MaGGiE

The objective is to develop a domain decomposition method via overlapping/embedding the component grids, which is to be used by upwind, multi-grid, finite volume solution algorithms. A computer code, given the name MaGGiE (Multi-Geometry Grid Embedder) is developed to meet this objective. MaGGiE takes independently generated component grids as input, and automatically constructs the composite mesh and interpolation data, which can be used by the finite volume solution methods with or without multigrid convergence acceleration. Six demonstrative examples showing various aspects of the overlap technique are presented and discussed. These cases are used for developing the procedure for overlapping grids of different topologies, and to evaluate the grid connection and interpolation data for finite volume calculations on a composite mesh. Time fluxes are transferred between mesh interfaces using a trilinear interpolation procedure. Conservation losses are minimal at the interfaces using this method. The multi-grid solution algorithm, using the coaser grid connections, improves the convergence time history as compared to the solution on composite mesh without multi-gridding

The ALADIN system and its canonical model configurations AROME CY41T1 and ALARO CY40T1

The ALADIN System is a numerical weather prediction (NWP) system developed by the international ALADIN consortium for operational weather forecasting and research purposes. It is based on a code that is shared with the global model IFS of the ECMWF and the ARPEGE model of Meteo-France. Today, this system can be used to provide a multitude of high-resolution limited-area model (LAM) configurations. A few configurations are thoroughly validated and prepared to be used for the operational weather forecasting in the 16 partner institutes of this consortium. These configurations are called the ALADIN canonical model configurations (CMCs). There are currently three CMCs: the ALADIN baseline CMC, the AROME CMC and the ALARO CMC. Other configurations are possible for research, such as process studies and climate simulations. The purpose of this paper is (i) to define the ALADIN System in relation to the global counterparts IFS and ARPEGE, (ii) to explain the notion of the CMCs, (iii) to document their most recent versions, and (iv) to illustrate the process of the validation and the porting of these configurations to the operational forecast suites of the partner institutes of the ALADIN consortium. This paper is restricted to the forecast model only; data assimilation techniques and postprocessing techniques are part of the ALADIN System but they are not discussed here

Computational Methods in Science and Engineering : Proceedings of the Workshop SimLabs@KIT, November 29 - 30, 2010, Karlsruhe, Germany

In this proceedings volume we provide a compilation of article contributions equally covering applications from different research fields and ranging from capacity up to capability computing. Besides classical computing aspects such as parallelization, the focus of these proceedings is on multi-scale approaches and methods for tackling algorithm and data complexity. Also practical aspects regarding the usage of the HPC infrastructure and available tools and software at the SCC are presented

Dataset for Automated Fact Checking in Czech Language

Naše práce prozkoumává existující datové sady pro úlohu automatického faktického ověřování textového tvrzení a navrhuje dvě metody jejich získávání v Českém jazyce. Nejprve předkládá rozsáhlý dataset FEVER CS se 127K anotovaných tvrzení pomocí strojového překladu datové sady v angličtině. Poté navrhuje sadu anotačních experimentů pro sběr nativního českého datasetu nad znalostní bází archivu ČTK a provádí ji se skupinou 163 studentů FSV UK, se ziskem 3,295 křížově anotovaných tvrzení s čtyřcestnou Fleissovou Kappa-shodou 0.63. Dále demonstruje vhodnost datové sady pro trénování modelů pro klasifikaci inference v přirozeném jazyce natrénováním modelu XLM-RoBERTa dosahujícího 85.5% mikro-F1 přesnosti v úloze klasifikace pravdivosti tvrzení z textového kontextu.Our work examines the existing datasets for the task of automated fact-verification of textual claims and proposes two methods of their acquisition in the low-resource Czech language. It first delivers a large-scale FEVER CS dataset of 127K annotated claims by applying the Machine Translation methods to a dataset available in English. It then designs a set of human-annotation experiments for collecting a novel dataset in Czech, using the ČTK Archive corpus for a knowledge base, and conducts them with a group of 163 students of FSS CUNI, yielding a dataset of 3,295 cross-annotated claims with a 4-way Fleiss' Kappa-agreement of 0.63. It then proceeds to show the eligibility of the dataset for training the Czech Natural Language Inference models, training an XLM-RoBERTa model scoring 85.5% micro-F1 in the task of classifying the claim veracity given textual evidence